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Registro Completo |
Biblioteca(s): |
Embrapa Florestas. |
Data corrente: |
24/10/2012 |
Data da última atualização: |
20/02/2015 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
RESENDE JUNIOR, M. F. R.; MUÑOZ, P.; RESENDE, M. D. V. de; GARRICK, D. J.; FERNANDO, R. L.; DAVIS, J. M.; JOKELA, E. J.; MARTIN, T. A.; PETER, G. F.; KIRST, M. |
Afiliação: |
M. F. R. RESENDE JUNIOR, UNIVERSITY OF FLORIDA; P. MUÑOZ, UNIVERSITY OF FLORIDA; MARCOS DEON VILELA DE RESENDE, CNPF; D. J. GARRICK, IOWA STATE UNIVERSITY; R. L. FERNANDO, IOWA STATE UNIVERSITY; J. M. DAVIS, UNIVERSITY OF FLORIDA; E. J. JOKELA, UNIVERSITY OF FLORIDA; T. A. MARTIN, UNIVERSITY OF FLORIDA; G. F. PETER, UNIVERSITY OF FLORIDA; M. KIRST, UNIVERSITY OF FLORIDA. |
Título: |
Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.) |
Ano de publicação: |
2012 |
Fonte/Imprenta: |
Genetics, v. 190, p. 1503-1510, April 2012. |
Idioma: |
Inglês |
Conteúdo: |
Genomic selection can increase genetic gain per generation through early selection. Genomic selection is expected to be particularly valuable for traits that are costly to phenotype and expressed late in the life cycle of long-lived species. Alternative approaches to genomic selection prediction models may perform differently for traits with distinct genetic properties. Here the performance of four different original methods of genomic selection that differ with respect to assumptions regarding distribution of marker effects, including (i) ridge regression–best linear unbiased prediction (RR–BLUP), (ii) Bayes A, (iii) Bayes Cp, and (iv) Bayesian LASSO are presented. In addition, a modified RR–BLUP (RR–BLUP B) that utilizes a selected subset of markers was evaluated. The accuracy of these methods was compared across 17 traits with distinct heritabilities and genetic architectures, including growth, development, and disease-resistance properties, measured in a Pinus taeda (loblolly pine) training population of 951 individuals genotyped with 4853 SNPs. The predictive ability of the methods was evaluated using a 10-fold, cross-validation approach, and differed only marginally for most method/trait combinations. Interestingly, for fusiform rust disease-resistance traits, Bayes Cp, Bayes A, and RR–BLUB B had higher predictive ability than RR–BLUP and Bayesian LASSO. Fusiform rust is controlled by few genes of large effect. A limitation of RR–BLUP is the assumption of equal contribution of all markers to the observed variation. However, RR-BLUP B performed equally well as the Bayesian approaches.The genotypic and phenotypic data used in this study are publically available for comparative analysis of genomic selection prediction models. MenosGenomic selection can increase genetic gain per generation through early selection. Genomic selection is expected to be particularly valuable for traits that are costly to phenotype and expressed late in the life cycle of long-lived species. Alternative approaches to genomic selection prediction models may perform differently for traits with distinct genetic properties. Here the performance of four different original methods of genomic selection that differ with respect to assumptions regarding distribution of marker effects, including (i) ridge regression–best linear unbiased prediction (RR–BLUP), (ii) Bayes A, (iii) Bayes Cp, and (iv) Bayesian LASSO are presented. In addition, a modified RR–BLUP (RR–BLUP B) that utilizes a selected subset of markers was evaluated. The accuracy of these methods was compared across 17 traits with distinct heritabilities and genetic architectures, including growth, development, and disease-resistance properties, measured in a Pinus taeda (loblolly pine) training population of 951 individuals genotyped with 4853 SNPs. The predictive ability of the methods was evaluated using a 10-fold, cross-validation approach, and differed only marginally for most method/trait combinations. Interestingly, for fusiform rust disease-resistance traits, Bayes Cp, Bayes A, and RR–BLUB B had higher predictive ability than RR–BLUP and Bayesian LASSO. Fusiform rust is controlled by few genes of large effect. A limitation of RR–BLUP is the assumption of equal contrib... Mostrar Tudo |
Palavras-Chave: |
Precisão. |
Thesagro: |
Pinus Taeda; Seleção Genética. |
Categoria do assunto: |
-- |
Marc: |
LEADER 02528naa a2200265 a 4500 001 1937733 005 2015-02-20 008 2012 bl uuuu u00u1 u #d 100 1 $aRESENDE JUNIOR, M. F. R. 245 $aAccuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.)$h[electronic resource] 260 $c2012 520 $aGenomic selection can increase genetic gain per generation through early selection. Genomic selection is expected to be particularly valuable for traits that are costly to phenotype and expressed late in the life cycle of long-lived species. Alternative approaches to genomic selection prediction models may perform differently for traits with distinct genetic properties. Here the performance of four different original methods of genomic selection that differ with respect to assumptions regarding distribution of marker effects, including (i) ridge regression–best linear unbiased prediction (RR–BLUP), (ii) Bayes A, (iii) Bayes Cp, and (iv) Bayesian LASSO are presented. In addition, a modified RR–BLUP (RR–BLUP B) that utilizes a selected subset of markers was evaluated. The accuracy of these methods was compared across 17 traits with distinct heritabilities and genetic architectures, including growth, development, and disease-resistance properties, measured in a Pinus taeda (loblolly pine) training population of 951 individuals genotyped with 4853 SNPs. The predictive ability of the methods was evaluated using a 10-fold, cross-validation approach, and differed only marginally for most method/trait combinations. Interestingly, for fusiform rust disease-resistance traits, Bayes Cp, Bayes A, and RR–BLUB B had higher predictive ability than RR–BLUP and Bayesian LASSO. Fusiform rust is controlled by few genes of large effect. A limitation of RR–BLUP is the assumption of equal contribution of all markers to the observed variation. However, RR-BLUP B performed equally well as the Bayesian approaches.The genotypic and phenotypic data used in this study are publically available for comparative analysis of genomic selection prediction models. 650 $aPinus Taeda 650 $aSeleção Genética 653 $aPrecisão 700 1 $aMUÑOZ, P. 700 1 $aRESENDE, M. D. V. de 700 1 $aGARRICK, D. J. 700 1 $aFERNANDO, R. L. 700 1 $aDAVIS, J. M. 700 1 $aJOKELA, E. J. 700 1 $aMARTIN, T. A. 700 1 $aPETER, G. F. 700 1 $aKIRST, M. 773 $tGenetics$gv. 190, p. 1503-1510, April 2012.
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Registro original: |
Embrapa Florestas (CNPF) |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Soja. Para informações adicionais entre em contato com valeria.cardoso@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Soja. |
Data corrente: |
19/02/2009 |
Data da última atualização: |
27/07/2011 |
Tipo da produção científica: |
Artigo em Anais de Congresso |
Autoria: |
OLIVEIRA, M. A. de; LIMA, D. de; BODNAR, A.; PELIZZARRO, E. C.; OLIVEIRA, F. F. de; SOUSA, R. L. de. |
Afiliação: |
Marcelo Alvares de Oliveira, CNPSo; Divania de Lima Embrapa Transferência de Tecnologia Londrina - PR; A. Bodnar, Emater; Enoir C. Pellizzaro Cvale Palotina PR; F. F. de Oliveira, Copacol; R. L. de Sousa, Coopavel. |
Título: |
Determinação de resíduos de pesticidas em grãos de soja produzidos sob normas de produção integrada. |
Ano de publicação: |
2008 |
Fonte/Imprenta: |
In: SIMPÓSIO DE SEGURANÇA ALIMENTAR, 2., 2008, Bento Gonçalves. Debatendo qualidade: anais. Bento Gonçalves: SBCTA-RS, 2008. |
Descrição Física: |
1 CD-ROM. |
Idioma: |
Português |
Palavras-Chave: |
Produção integrada de soja. |
Categoria do assunto: |
-- |
Marc: |
LEADER 00673naa a2200193 a 4500 001 1471313 005 2011-07-27 008 2008 bl --- 0-- u #d 100 1 $aOLIVEIRA, M. A. de 245 $aDeterminação de resíduos de pesticidas em grãos de soja produzidos sob normas de produção integrada. 260 $c2008 300 $c1 CD-ROM. 653 $aProdução integrada de soja 700 1 $aLIMA, D. de 700 1 $aBODNAR, A. 700 1 $aPELIZZARRO, E. C. 700 1 $aOLIVEIRA, F. F. de 700 1 $aSOUSA, R. L. de 773 $tIn: SIMPÓSIO DE SEGURANÇA ALIMENTAR, 2., 2008, Bento Gonçalves. Debatendo qualidade: anais. Bento Gonçalves: SBCTA-RS, 2008.
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